Search results for: energy detection

Authors: Nurhak Altın, Ayhan Kucukmanisa, Oguzhan Urhan

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It is important that highways are in good condition for traffic safety. Road crashes (road cracks, erosion of lane markings, etc.) can cause accidents by affecting driving. Image processing based methods for detecting road cracks are available in the literature. In this paper, a deep learning based road crack detection approach is proposed. YOLO (You Look Only Once) is adopted as core component of the road crack detection approach presented. The YOLO network structure, which is developed for object detection, is trained with road crack images as a new class that is not previously used in YOLO. The performance of the proposed method is compared using different training methods: using randomly generated weights and training their own pre-trained weights (transfer learning). A similar training approach is applied to the simplified version of the YOLO network model (tiny yolo) and the results of the performance are examined. The developed system is able to process 8 fps on NVIDIA Jetson TX1 development kit.

Keywords: deep learning, embedded platform, real-time processing, road crack detection

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Authors: Aria Vitkova, Hanna Sykulska-Lawrence

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In recent years, Europa has been one of the major focus points in astrobiology due to its high potential of harbouring life in the vast ocean underneath its icy crust. However, the detection of life on Europa faces many challenges due to the harsh environmental conditions and mission constraints. Raman spectroscopy is a highly capable and versatile in-situ characterisation technique that does not require any sample preparation. It has only been used on Earth to date; however, recent advances in optical and laser technology have also allowed it to be considered for extraterrestrial exploration. So far, most efforts have been focused on the exploration of Mars, the most imminent planetary target. However, as an emerging technology with high miniaturization potential, Raman spectroscopy also represents a promising tool for the exploration of Europa. In this study, the capabilities of Raman technology in terms of life detection on Europa are explored and assessed. Spectra of biosignatures identified as high priority molecular targets for life detection on Europa were acquired at various excitation wavelengths and conditions analogous to Europa. The effects of extremely low temperatures and low concentrations in water ice were explored and evaluated in terms of the effectiveness of various configurations of Raman instruments. Based on the findings, a design of a miniaturized Raman instrument optimized for in-situ detection of life on Europa is proposed.

Keywords: astrobiology, biosignatures, Europa, life detection, Raman Spectroscopy

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Authors: Mohammad Besharatloo

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Intrusion detection is an important research topic in network security because of increasing growth in the use of computer network services. Intrusion detection is done with the aim of detecting the unauthorized use or abuse in the networks and systems by the intruders. Therefore, the intrusion detection system is an efficient tool to control the user's access through some predefined regulations. Since, the data used in intrusion detection system has high dimension, a proper representation is required to show the basis structure of this data. Therefore, it is necessary to eliminate the redundant features to create the best representation subset. In the proposed method, a hybrid model of differential evolution and firefly algorithms was employed to choose the best subset of properties. In addition, decision tree and support vector machine (SVM) are adopted to determine the quality of the selected properties. In the first, the sorted population is divided into two sub-populations. These optimization algorithms were implemented on these sub-populations, respectively. Then, these sub-populations are merged to create next repetition population. The performance evaluation of the proposed method is done based on KDD Cup99. The simulation results show that the proposed method has better performance than the other methods in this context.

Keywords: intrusion detection system, differential evolution, firefly algorithm, support vector machine, decision tree

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Authors: Mahmoud E. Mohamed, Ahmed F. Shalash, Hanan A. Kamal

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In communication systems, frequency jump is a serious problem caused by the oscillators used. Kalman filters are used to detect that jump, Despite the tradeoff between the noise level and the speed of the detection. In this paper, An improvement is introduced in the Kalman filter, Through a nonlinear change in the bandwidth of the filter. Simulation results show a considerable improvement in the filter speed with a very low noise level. Additionally, The effect on the response to false alarms is also presented and false alarm rate show improvement.

Keywords: Kalman filter, innovation, false detection, improvement

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Authors: Sukhleen Kaur

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In security groundwork, Intrusion Detection System (IDS) has become an important component. The IDS has received increasing attention in recent years. IDS is one of the effective way to detect different kinds of attacks and malicious codes in a network and help us to secure the network. Data mining techniques can be implemented to IDS, which analyses the large amount of data and gives better results. Data mining can contribute to improving intrusion detection by adding a level of focus to anomaly detection. So far the study has been carried out on finding the attacks but this paper detects the malicious files. Some intruders do not attack directly, but they hide some harmful code inside the files or may corrupt those file and attack the system. These files are detected according to some defined parameters which will form two lists of files as normal files and harmful files. After that data mining will be performed. In this paper a hybrid classifier has been used via Naive Bayes and Ripper classification methods. The results show how the uploaded file in the database will be tested against the parameters and then it is characterised as either normal or harmful file and after that the mining is performed. Moreover, when a user tries to mine on harmful file it will generate an exception that mining cannot be made on corrupted or harmful files.

Keywords: data mining, association, classification, clustering, decision tree, intrusion detection system, misuse detection, anomaly detection, naive Bayes, ripper

Procedia PDF Downloads 395

Authors: Kate Smith, Shuming Liu, Yi Liu, Dragan Savic, Gustaf Olsson, Tian Chang, Xue Wu

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In a water supply system, a great deal of care goes into sourcing, treating and delivering water to consumers, but less thought is given to the energy consumed during these processes. This study uses 2011 data to quantify energy use for urban water supply in China and investigates population density as a possible influencing factor. The objective is to provide information that can be used to develop energy-conscious water infrastructure policy, calculate the energy co-benefits of water conservation and compare energy use between China and other countries. The average electrical energy intensity and per capita electrical energy consumption for urban water supply in China in 2011 were 0.29 kWh/m3 and 33.2 kWh/cap•yr, respectively. Comparison between provinces revealed a direct correlation between energy intensity of urban water supply and population served per unit length of pipe. This could imply energy intensity is lower when more densely populated areas are supplied by relatively dense networks of pipes. This study also found that whereas the percentage of energy used for urban water supply tends to increase with the percentage of population served this increase is slower where water supply is more energy efficient and where a larger percentage of population is already supplied.

Keywords: china, electrical energy use, water-energy nexus, water supply

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Authors: Andra Blumberga, Uldis Bariss, Anna Kubule, Dagnija Blumberga

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European Union Energy Efficiency Directive provides a set of binding energy efficiency measures to reach. Each of the member states can use either energy efficiency obligation scheme or alternative policy measures or combination of both. Latvian government has decided to divide savings among obligation scheme (65%) and alternative measures (35%). This decision might lead to significant energy tariff increase hence impact on the national economy. To assess impact of alternative policy measures focusing on energy management scheme based on ISO 50001 and ability to decrease share of obligation scheme a System Dynamics modeling was used. Simulation results show that energy efficiency goal can be met with alternative policy measure to large energy consumers in industrial, tertiary and public sectors by applying the energy tax exemption for implementers of energy management system. A delay in applying alternative policy measures plays very important role in reaching the energy efficiency goal. One year delay in implementation of this policy measure reduces cumulative energy savings from 2016 to 2017 from 5200 GWh to 3000 GWh in 2020.

Keywords: system dynamics, energy efficiency, policy measure, energy management system, obligation scheme

Procedia PDF Downloads 255

Authors: Omar Elharrouss, Youssef Hmamouche, Assia Kamal Idrissi, Btissam El Khamlichi, Amal El Fallah-Seghrouchni

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Edge detection is represented as one of the most challenging tasks in computer vision, due to the complexity of detecting the edges or boundaries in real-world images that contains objects of different types and scales like trees, building as well as various backgrounds. Edge detection is represented also as a key task for many computer vision applications. Using a set of backbones as well as attention modules, deep-learning-based methods improved the detection of edges compared with the traditional methods like Sobel and Canny. However, images of complex scenes still represent a challenge for these methods. Also, the detected edges using the existing approaches suffer from non-refined results while the image output contains many erroneous edges. To overcome this, n this paper, by using the mechanism of residual learning, a refined edge detection network is proposed (RED-Net). By maintaining the high resolution of edges during the training process, and conserving the resolution of the edge image during the network stage, we make the pooling outputs at each stage connected with the output of the previous layer. Also, after each layer, we use an affined batch normalization layer as an erosion operation for the homogeneous region in the image. The proposed methods are evaluated using the most challenging datasets including BSDS500, NYUD, and Multicue. The obtained results outperform the designed edge detection networks in terms of performance metrics and quality of output images.

Keywords: edge detection, convolutional neural networks, deep learning, scale-representation, backbone

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Authors: Amir Sattari

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For newly produced houses and energy renovations, an energy calculation needs to be conducted. This is done to verify whether the energy consumption criteria of the house -to reach the energy targets by 2020 and 2050- are in-line with the norms. The main purpose of this study is to confirm whether easy to use energy calculation software or hand calculations used by small companies or individuals give logical results compared to advanced energy simulation program used by researchers or bigger companies. There are different methods for calculating energy consumption. In this paper, two energy calculation programs are used and the relation of energy consumption with solar radiation is compared. A hand calculation is also done to validate whether the hand calculations are still reasonable. The two computer programs which have been used are TMF Energi (the easy energy calculation variant used by small companies or individuals) and IDA ICE - Indoor Climate and Energy (the advanced energy simulation program used by researchers or larger companies). The calculations are done for a standard house from the Swedish house supplier Fiskarhedenvillan. The method is based on having the same conditions and inputs in the different calculation forms so that the results can be compared and verified. The house has been faced differently to see how the orientation affects energy consumption in different methods. The results for the simulations are close to each other and the hand calculation differs from the computer programs by only 5%. Even if solar factors differ due to the orientation of the house, energy calculation results from different computer programs and even hand calculation methods are in line with each other.

Keywords: energy calculation, energy consumption, energy simulation, IDA ICE, TMF energi

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Authors: Abdelghani Chahmi

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This article examines the detection and localization of faults in electrical systems, particularly those using asynchronous machines. First, the process of failure will be characterized, relevant symptoms will be defined and based on those processes and symptoms, a model of those malfunctions will be obtained. Second, the development of the diagnosis of the machine will be shown. As studies of malfunctions in electrical systems could only rely on a small amount of experimental data, it has been essential to provide ourselves with simulation tools which allowed us to characterize the faulty behavior. Fault detection uses signal processing techniques in known operating phases.

Keywords: induction motor, modeling, bearing damage, airgap eccentricity, torque variation

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Authors: Hussin K. Ragb, Vijayan K. Asari

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In this paper, we present a pedestrian detection descriptor called Fused Structure and Texture (FST) features based on the combination of the local phase information with the texture features. Since the phase of the signal conveys more structural information than the magnitude, the phase congruency concept is used to capture the structural features. On the other hand, the Center-Symmetric Local Binary Pattern (CSLBP) approach is used to capture the texture information of the image. The dimension less quantity of the phase congruency and the robustness of the CSLBP operator on the flat images, as well as the blur and illumination changes, lead the proposed descriptor to be more robust and less sensitive to the light variations. The proposed descriptor can be formed by extracting the phase congruency and the CSLBP values of each pixel of the image with respect to its neighborhood. The histogram of the oriented phase and the histogram of the CSLBP values for the local regions in the image are computed and concatenated to construct the FST descriptor. Several experiments were conducted on INRIA and the low resolution DaimlerChrysler datasets to evaluate the detection performance of the pedestrian detection system that is based on the FST descriptor. A linear Support Vector Machine (SVM) is used to train the pedestrian classifier. These experiments showed that the proposed FST descriptor has better detection performance over a set of state of the art feature extraction methodologies.

Keywords: pedestrian detection, phase congruency, local phase, LBP features, CSLBP features, FST descriptor

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Authors: Abdelhak Bouchakour, Mustafa Brahami, Layachi Zaghba

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The use of photovoltaic energy offers an inexhaustible supply of energy but also a clean and non-polluting energy, which is a definite advantage. The geographical location of Algeria promotes the development of the use of this energy. Indeed, given the importance of the intensity of the radiation received and the duration of sunshine. For this reason, the objective of our work is to develop a data-processing tool (software) of calculation and optimization of dimensioning of the photovoltaic installations. Our approach of optimization is basing on mathematical models, which amongst other things describe the operation of each part of the installation, the energy production, the storage and the consumption of energy.

Keywords: solar panel, solar radiation, inverter, optimization

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Authors: Mauricio George Miguel Jardini, Jose Antonio Jardini

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Transmission power utilities participate with kilometers of circuits, many with particularities in terms of vegetation growth. To control these rights-of-way, maintenance teams perform ground, and air inspections, and the identification method is subjective (indirect). On a ground inspection, when identifying an irregularity, for example, high vegetation threatening contact with the conductor cable, pruning or suppression is performed immediately. In an aerial inspection, the suppression team is mobilized to the identified point. This work investigates the use of 3D modeling of a transmission line segment using RGB (red, blue, and green) images and LiDAR (Light Detection and Ranging) sensor data. Both sensors are coupled to unmanned aerial vehicle. The goal is the accurate and timely detection of vegetation along the right-of-way that can cause shutdowns.

Keywords: 3D modeling, LiDAR, right-of-way, transmission lines, vegetation

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Authors: Vishal Kumar, Soumitra Satapathi

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Föster Resonance Energy Transfer (FRET) is a powerful technique used to probe close-range molecular interactions. Physically, the FRET phenomenon manifests as a dipole–dipole interaction between closely juxtaposed fluorescent molecules (10–100 Å). Our effort is to employ this FRET technique to make a prototype device for highly sensitive detection of environment pollutant. Among the most common environmental pollutants, nitroaromatic compounds (NACs) are of particular interest because of their durability and toxicity. That’s why, sensitive and selective detection of small amounts of nitroaromatic explosives, in particular, 2,4,6-trinitrophenol (TNP), 2,4-dinitrotoluene (DNT) and 2,4,6-trinitrotoluene (TNT) has been a critical challenge due to the increasing threat of explosive-based terrorism and the need of environmental monitoring of drinking and waste water. In addition, the excessive utilization of TNP in several other areas such as burn ointment, pesticides, glass and the leather industry resulted in environmental accumulation, and is eventually contaminating the soil and aquatic systems. To the date, high number of elegant methods, including fluorimetry, gas chromatography, mass, ion-mobility and Raman spectrometry have been successfully applied for explosive detection. Among these efforts, fluorescence-quenching methods based on the mechanism of FRET show good assembly flexibility, high selectivity and sensitivity. Here, we report a FRET-based sensor system for the highly selective detection of NACs, such as TNP, DNT and TNT. The sensor system is composed of a copolymer Poly [(N,N-dimethylacrylamide)-co-(Boc-Trp-EMA)] (RP) bearing tryptophan derivative in the side chain as donor and dansyl tagged copolymer P(MMA-co-Dansyl-Ala-HEMA) (DCP) as an acceptor. Initially, the inherent fluorescence of RP copolymer is quenched by non-radiative energy transfer to DCP which only happens once the two molecules are within Förster critical distance (R0). The excellent spectral overlap (Jλ= 6.08×10¹⁴ nm⁴M⁻¹cm⁻¹) between donors’ (RP) emission profile and acceptors’ (DCP) absorption profile makes them an exciting and efficient FRET pair i.e. further confirmed by the high rate of energy transfer from RP to DCP i.e. 0.87 ns⁻¹ and lifetime measurement by time correlated single photon counting (TCSPC) to validate the 64% FRET efficiency. This FRET pair exhibited a specific fluorescence response to NACs such as DNT, TNT and TNP with 5.4, 2.3 and 0.4 µM LODs, respectively. The detection of NACs occurs with high sensitivity by photoluminescence quenching of FRET signal induced by photo-induced electron transfer (PET) from electron-rich FRET pair to electron-deficient NAC molecules. The estimated stern-volmer constant (KSV) values for DNT, TNT and TNP are 6.9 × 10³, 7.0 × 10³ and 1.6 × 104 M⁻¹, respectively. The mechanistic details of molecular interactions are established by time-resolved fluorescence, steady-state fluorescence and absorption spectroscopy confirmed that the sensing process is of mixed type, i.e. both dynamic and static quenching as lifetime of FRET system (0.73 ns) is reduced to 0.55, 0.57 and 0.61 ns DNT, TNT and TNP, respectively. In summary, the simplicity and sensitivity of this novel FRET sensor opens up the possibility of designing optical sensor of various NACs in one single platform for developing multimodal sensor for environmental monitoring and future field based study.

Keywords: FRET, nitroaromatic, stern-Volmer constant, tryptophan and dansyl tagged copolymer

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Authors: Priyanka Bhatnagar, Malkeshkumar Patel, Joondong Kim, Joonpyo Hong

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Artificial skin and sensory memory platforms are produced using a flexible, transparent photovoltaic (TPV) device. The TPV device is composed of a metal oxide heterojunction (nZnO/p-NiO) and transmits visible light (> 50%) while producing substantial electric power (0.5 V and 200 μA cm-2 ). This TPV device is a transparent energy interface that can be used to detect signals and propagate information without an external energy supply. The TPV artificial skin offers a temperature detection range (0 C75 C) that is wider than that of natural skin (5 C48 °C) due to the temperature-sensitive pyrocurrent from the ZnO layer. Moreover, the TPV thermoreceptor offers sensory memory of extreme thermal stimuli. Much like natural skin, artificial skin uses the nociceptor mechanism to protect tissue from harmful damage via signal amplification (hyperalgesia) and early adaption (allodynia). This demonstrates the many features of TPV artificial skin, which can sense and transmit signals and memorize information under self-operation mode. This transparent photovoltaic skin can provide sustainable energy for use in human electronics.

Keywords: transparent, photovoltaics, thermal memory, artificial skin, thermoreceptor

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Authors: N. Ghatwary, A. Ahmed, H. Jalab

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In this paper, an approach for the liver tumor detection in computed tomography (CT) images is represented. The detection process is based on classifying the features of target liver cell to either tumor or non-tumor. Fractional differential (FD) is applied for enhancement of Liver CT images, with the aim of enhancing texture and edge features. Later on, a fusion method is applied to merge between the various enhanced images and produce a variety of feature improvement, which will increase the accuracy of classification. Each image is divided into NxN non-overlapping blocks, to extract the desired features. Support vector machines (SVM) classifier is trained later on a supplied dataset different from the tested one. Finally, the block cells are identified whether they are classified as tumor or not. Our approach is validated on a group of patients’ CT liver tumor datasets. The experiment results demonstrated the efficiency of detection in the proposed technique.

Keywords: fractional differential (FD), computed tomography (CT), fusion, aplha, texture features.

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Authors: Mar Cañada Soriano, Rafael Royo-Pastor, Carolina Aparicio-Fernández, Jose-Luis Vivancos

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The lack of insulation, along with the existence of air leakages, constitute a meaningful impact on the energy performance of buildings. Both of them lead to increases in the energy demand through additional heating and/or cooling loads. Additionally, they cause thermal discomfort. In order to quantify these uncontrolled air currents, pressurization and depressurization tests can be performed. Among them, the Blower Door test is a standardized procedure to determine the airtightness of a space which characterizes the rate of air leakages through the envelope surface, calculating to this purpose an air flow rate indicator. In this sense, the low-energy buildings complying with the Passive House design criteria are required to achieve high levels of airtightness. Due to the invisible nature of air leakages, additional tools are often considered to identify where the infiltrations take place. Among them, the infrared thermography entails a valuable technique to this purpose since it enables their detection. The aim of this study is to assess the airtightness of a typical Mediterranean dwelling house located in the Valencian orchad (Spain) restored under the Passive House standard using to this purpose the blower-door test. Moreover, the building energy performance modelling tools TRNSYS (TRaNsient System Simulation program) and TRNFlow (TRaNsient Flow) have been used to determine its energy performance, and the infiltrations’ identification was carried out by means of infrared thermography. The low levels of infiltrations obtained suggest that this house may comply with the Passive House standard.

Keywords: airtightness, blower door, trnflow, infrared thermography

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Authors: Ali A. Aldosari

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Change detection of Earth surface features is extremely important for better understanding of our environment in order to promote better decision making. Al-Jawf is remarkable for its abundant agricultural water where there is fertile agricultural land due largely to underground water. As result, this region has large areas of cultivation of dates, olives and fruits trees as well as other agricultural products such as Alfa Alfa and wheat. However this agricultural area was declined due to the reduction of government supports in the last decade. This reduction was not officially recorded or measured in this region at large scale or governorate level. Remote sensing data are primary sources extensively used for change detection in agriculture applications. This study is applied the technology of GIS and used the Normalized Difference Vegetation Index (NDVI) which can be used to measure and analyze the spatial and temporal changes in the agriculture areas in the Aljouf region.

Keywords: spatial analysis, geographical information system, change detection

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Authors: Duc V. Nguyen

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Induction motors are widely used in different industry areas and can experience various kinds of faults in stators and rotors. In general, fault detection and diagnosis techniques for induction motors can be supervised by measuring quantities such as noise, vibration, and temperature. The installation of mechanical sensors in order to assess the health conditions of a machine is typically only done for expensive or load-critical machines, where the high cost of a continuous monitoring system can be Justified. Nevertheless, induced current monitoring can be implemented inexpensively on machines with arbitrary sizes by using current transformers. In this regard, effective and low-cost fault detection techniques can be implemented, hence reducing the maintenance and downtime costs of motors. This work proposes a method for fault detection and diagnosis of induction motors, which combines classical fast Fourier transform and modern/advanced machine learning techniques. The proposed method is validated on real-world data and achieves a precision of 99.7% for fault detection and 100% for fault classification with minimal expert knowledge requirement. In addition, this approach allows users to be able to optimize/balance risks and maintenance costs to achieve the highest benet based on their requirements. These are the key requirements of a robust prognostics and health management system.

Keywords: fault detection, FFT, induction motor, predictive maintenance

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Authors: Abdelkhalek Bouchikhi, Elyes Benmokhtar, Sebastien Saletzki

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The aeronautical field is experiencing issues with RF spectrum congestion due to the constant increase in the number of flights, aircrafts and telecom systems on board. In addition, these systems are bulky in size, weight and energy consumption. The cognitive radio helps particularly solving the spectrum congestion issue by its capacity to detect idle frequency channels then, allowing an opportunistic exploitation of the RF spectrum. The present work aims to propose a new use case for aeronautical spectrum sharing and to study the performances of three different detection techniques: energy detector, matched filter and cyclostationary detector within the aeronautical use case. The spectrum in the proposed cognitive radio is allocated dynamically where each cognitive radio follows a cognitive cycle. The spectrum sensing is a crucial step. The goal of the sensing is gathering data about the surrounding environment. Cognitive radio can use different sensors: antennas, cameras, accelerometer, thermometer, etc. In IEEE 802.22 standard, for example, a primary user (PU) has always the priority to communicate. When a frequency channel witch used by the primary user is idle, the secondary user (SU) is allowed to transmit in this channel. The Distance Measuring Equipment (DME) is composed of a UHF transmitter/receiver (interrogator) in the aircraft and a UHF receiver/transmitter on the ground. While the future cognitive radio will be used jointly to alleviate the spectrum congestion issue in the aeronautical field. LDACS, for example, is a good candidate; it provides two isolated data-links: ground-to-air and air-to-ground data-links. The first contribution of the present work is a strategy allowing sharing the L-band. The adopted spectrum sharing strategy is as follow: the DME will play the role of PU which is the licensed user and the LDACS1 systems will be the SUs. The SUs could use the L-band channels opportunely as long as they do not causing harmful interference signals which affect the QoS of the DME system. Although the spectrum sensing is a key step, it helps detecting holes by determining whether the primary signal is present or not in a given frequency channel. A missing detection on primary user presence creates interference between PU and SU and will affect seriously the QoS of the legacy radio. In this study, first brief definitions, concepts and the state of the art of cognitive radio will be presented. Then, a study of three communication channel detection algorithms in a cognitive radio context is carried out. The study is made from the point of view of functions, material requirements and signal detection capability in the aeronautical field. Then, we presented a modeling of the detection problem by three different methods (energy, adapted filter, and cyclostationary) as well as an algorithmic description of these detectors is done. Then, we study and compare the performance of the algorithms. Simulations were carried out using MATLAB software. We analyzed the results based on ROCs curves for SNR between -10dB and 20dB. The three detectors have been tested with a synthetics and real world signals.

Keywords: aeronautic, communication, navigation, surveillance systems, cognitive radio, spectrum sensing, software defined radio

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Authors: Temesgen Geremew

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The excessive emission of heavy metal ions from industrial processes poses a serious threat to both the environment and human health. This study presents a distinct approach utilizing (PTh-MnS/CoS NPs) for the highly selective and sensitive detection of Hg²⁺ ions in water. Such detection is crucial for safeguarding human health, protecting the environment, and accurately assessing toxicity. The fabrication method employs a simple and efficient chemical precipitation technique, harmoniously combining polythiophene, MnS, and CoS NPs to create highly active substrates for SERS. The MnS@Hg²⁺ exhibits a distinct Raman shift at 1666 cm⁻¹, enabling specific identification and demonstrating the highest responsiveness among the studied semiconductor substrates with a detection limit of only 1 nM. This investigation demonstrates reliable and practical SERS detection for Hg²⁺ ions. Relative standard deviation (RSD) ranged from 0.49% to 9.8%, and recovery rates varied from 96% to 102%, indicating selective adsorption of Hg²⁺ ions on the synthesized substrate. Furthermore, this research led to the development of a remarkable set of substrates, including (MnS, CoS, MnS/CoS, and PTh-MnS/CoS) nanoparticles were created right there on SiO₂/Si substrate, all exhibiting sensitive, robust, and selective SERS for Hg²⁺ ion detection. These platforms effectively monitor Hg²⁺ concentrations in real environmental samples.

Keywords: surface-enhanced raman spectroscopy (SERS), sensor, mercury ions, nanoparticles, and polythiophene.

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Authors: Sheldon McCall, Miao Yu, Liyun Gong, Shigang Yue, Stefanos Kollias

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Falls are a significant health concern for older adults globally, and prompt identification is critical to providing necessary healthcare support. Our study proposes a new fall detection method using computer vision based on modern deep learning techniques. Our approach involves training a trans- former model on a large 2D pose dataset for general action recognition, followed by transfer learning. Specifically, we freeze the first few layers of the trained transformer model and train only the last two layers for fall detection. Our experimental results demonstrate that our proposed method outperforms both classical machine learning and deep learning approaches in fall/non-fall classification. Overall, our study suggests that our proposed methodology could be a valuable tool for identifying falls.

Keywords: healthcare, fall detection, transformer, transfer learning

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Authors: Bin Liu

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Protein remote homology detection and fold recognition are two most important tasks in protein sequence analysis, which is critical for protein structure and function studies. In this study, we combined the profile-based features with various string kernels, and constructed several computational predictors for protein remote homology detection and fold recognition. Experimental results on two widely used benchmark datasets showed that these methods outperformed the competing methods, indicating that these predictors are useful computational tools for protein sequence analysis. By analyzing the discriminative features of the training models, some interesting patterns were discovered, reflecting the characteristics of protein superfamilies and folds, which are important for the researchers who are interested in finding the patterns of protein folds.

Keywords: protein remote homology detection, protein fold recognition, profile-based features, Support Vector Machines (SVMs)

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Authors: T. V. Dinh, I. Y. Choi, J. W. Ahn, Y. H. Oh, G. Bo, J. Y. Lee, J. C. Kim

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A Non-Dispersive Infrared (NDIR) multi-gas analyzer has been developed to monitor the emission of carbon monoxide (CO) and sulfur dioxide (SO2) from various industries. The NDIR technique for gas measurement is based on the wavelength absorption in the infrared spectrum as a way to detect particular gasses. NDIR analyzers have popularly applied in the Tele-Monitoring System (TMS). The advantage of the NDIR analyzer is low energy consumption and cost compared with other spectroscopy methods. However, zero/span drift and interference are its urgent issues to be solved. Multi-pathway technique based on optical White cell was employed to improve the sensitivity of the analyzer in this work. A pyroelectric detector was used to detect the Infrared radiation. The analytical range of the analyzer was 0 ~ 200 ppm. The instrument response time was < 2 min. The detection limits of CO and SO2 were < 4 ppm and < 6 ppm, respectively. The zero and span drift of 24 h was less than 3%. The linearity of the analyzer was less than 2.5% of reference values. The precision and accuracy of both CO and SO2 channels were < 2.5% of relative standard deviation. In general, the analyzer performed well. However, the detection limit and 24h drift should be improved to be a more competitive instrument.

Keywords: analyzer, CEMS, monitoring, NDIR, TMS

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Authors: Francesca Scalisi, Cesare Sposito

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The building construction industry consumes a large amount of resources and energy, both during construction (embodied energy) and during the operational phase (operating energy). This paper presents a review of the literature on low carbon and low embodied energy materials in buildings. The embodied energy comprises the energy consumed during the extraction, processing, transportation, construction, and demolition of building materials. While designing a nearly zero energy building, it is necessary to choose and use materials, components, and technologies that allow to reduce the consumption of energy and also to reduce the emissions in the atmosphere during all the Life Cycle Assessment phases. The appropriate choice of building materials can contribute decisively to reduce the energy consumption of the building sector. The increasing worries for the environmental impact of construction materials are witnessed by a lot of studies. The mentioned worries have brought again the attention towards natural materials. The use of more sustainable construction materials and construction techniques represent a major contribution to the eco-efficiency of the construction industry and thus to a more sustainable development.

Keywords: embodied energy, embodied carbon, life cycle assessment, architecture, sustainability, material construction

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Authors: Noel Chellan

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Energy is the life-blood of development. All human societies have been and still are dependent on energy – some societies more than others. With regard to energy in South Africa, previous policies of the apartheid regime neglected the energy needs of poor black communities in general – and rural communities in particular. Since South Africa’s first democratic elections in 1994 – whilst millions of South African households have received electricity from the national electricity grid, there are still many rural communities that are still experiencing challenges in relation to both electricity deprivation as well as provision. This paper looks at the energy-mix of the Mnweni rural community in South Africa and argues that understanding energy is key to understanding the nature and forms of development of any community or country, for that matter. The paper engages with the energy trends in the rural community of Mnweni from the days of apartheid until 2021. It also looks at agricultural practises from an energy perspective. Such an energy perspective will enable one to assess the pace and scale of development in rural Mnweni.

Keywords: rural, energy, development, apartheid

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Authors: Izuru Nomura, Tatsuya Takino, Yuji Kageyama, Shin Nagata, Hiroyuki Kamata

Abstract:

We propose a method of crater detection from the image of the lunar surface captured by the small space probe. We use the principal component analysis (PCA) to detect craters. Nevertheless, considering　severe environment of the space, it is impossible to use generic computer in practice. Accordingly, we have to implement the method in FPGA. This paper compares FPGA and generic computer by the processing time of a method of crater detection using principal component analysis.

Keywords: crater, PCA, eigenvector, strength value, FPGA, processing time

Procedia PDF Downloads 531

Authors: Dinesh Gundavaram

Abstract:

This paper presents an investigation on bridge damage detection based on the dynamic responses estimated from a passing vehicle. A numerical simulation of steel truss bridge for railway was used in this investigation. The bridge response at different locations is measured using CSI-Bridge software. Several damage scenarios are considered including different locations and severities. The possibilities of dynamic properties of global modes in the identification of structural changes in truss bridges were discussed based on the results of measurement.

Keywords: bridge, damage, dynamic responses, detection

Procedia PDF Downloads 249

Authors: Nuur Ezaini Akmar Ismail, Norbazilah Rahim, Norul Huda Md Rasdi, Maslina Daud

Abstract:

A web application is the most targeted by the attacker because the web application is accessible by the end users. It has become more advantageous to the attacker since not all the end users aware of what kind of sensitive data already leaked by them through the Internet especially via social network in shake on ‘sharing’. The attacker can use this information such as personal details, a favourite of artists, a favourite of actors or actress, music, politics, and medical records to customize phishing attack thus trick the user to click on malware-laced attachments. The Phishing attack is one of the most popular attacks for social engineering technique against web applications. There are several methods to detect phishing websites such as Blacklist/Whitelist based detection, heuristic-based, and visual similarity-based detection. This paper illustrated a comparison between the heuristic-based technique using features of a uniform resource locator (URL) and visual similarity-based detection techniques that compares the content of a suspected phishing page with the legitimate one in order to detect new phishing sites based on the paper reviewed from the past few years. The comparison focuses on three indicators which are false positive and negative, accuracy of the method, and time consumed to detect phishing website.

Keywords: heuristic-based technique, phishing detection, social engineering and visual similarity-based technique

Procedia PDF Downloads 158

Authors: Juan Sepúlveda

Abstract:

Energy is a fundamental component in sustainability, the access and use of this resource is related with economic growth, social improvements, and environmental impacts. In this sense, energy efficiency has been studied as a factor that enhances the positive impacts of energy in communities; however, the implementation of efficiency requires strong policy and strategies that usually rely on individual measures focused in independent dimensions. In this paper, the problem of energy efficiency as a multi-objective problem is studied, using scientometric analysis to discover trends and patterns that allow to identify the main variables and study approximations related with a further development of models to integrate energy efficiency and MCA into policy making for small communities.

Keywords: energy efficiency, MCA, scientometric, trends

Procedia PDF Downloads 348